ICPC data
library(leaflet)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(readr)
library(sf)## Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUEworld <- st_read("data/world.shp")## Reading layer `world' from data source
## `/home/brayand/Storage/School/from-data-to-knowledge-interpretation-visualization-presentation-course/Homework 10/data/world.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 197 features and 63 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -180 ymin: -55.8917 xmax: 180 ymax: 83.59961
## Geodetic CRS: GCS_unknowndata <- read_csv("data/icpc-full.csv")## Rows: 2562 Columns: 21## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (10): Host, City, Venue, University, Country, Team, Contestant 1, Conte...
## dbl (6): Year, Rank, Score, Total, Score Percentage, Penalty
## lgl (4): Gold, Silver, Bronze, Honorable
## date (1): Date
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.host_counts <- data %>%
group_by(Host) %>%
summarise(Count = n()) %>%
ungroup()
print(world)## Simple feature collection with 197 features and 63 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -180 ymin: -55.8917 xmax: 180 ymax: 83.59961
## Geodetic CRS: GCS_unknown
## First 10 features:
## scalerank featurecla labelrank sovereignt sov_a3 adm0_dif
## 1 1 Admin-0 country 3 South Sudan SDS 0
## 2 1 Admin-0 country 3 Afghanistan AFG 0
## 3 1 Admin-0 country 3 Angola AGO 0
## 4 1 Admin-0 country 6 United Kingdom GB1 1
## 5 1 Admin-0 country 6 Albania ALB 0
## 6 3 Admin-0 country 6 Andorra AND 0
## 7 1 Admin-0 country 4 United Arab Emirates ARE 0
## 8 1 Admin-0 country 2 Argentina ARG 0
## 9 1 Admin-0 country 6 Armenia ARM 0
## 10 1 Admin-0 country 6 Antigua and Barbuda ATG 0
## level type admin adm0_a3 geou_dif
## 1 2 Sovereign country South Sudan SDS 0
## 2 2 Sovereign country Afghanistan AFG 0
## 3 2 Sovereign country Angola AGO 0
## 4 2 Dependency Anguilla AIA 0
## 5 2 Sovereign country Albania ALB 0
## 6 2 Sovereign country Andorra AND 0
## 7 2 Sovereign country United Arab Emirates ARE 0
## 8 2 Sovereign country Argentina ARG 0
## 9 2 Sovereign country Armenia ARM 0
## 10 2 Sovereign country Antigua and Barbuda ATG 0
## geounit gu_a3 su_dif subunit su_a3 brk_diff
## 1 South Sudan SDS 0 South Sudan SDS 0
## 2 Afghanistan AFG 0 Afghanistan AFG 0
## 3 Angola AGO 0 Angola AGO 0
## 4 Anguilla AIA 0 Anguilla AIA 0
## 5 Albania ALB 0 Albania ALB 0
## 6 Andorra AND 0 Andorra AND 0
## 7 United Arab Emirates ARE 0 United Arab Emirates ARE 0
## 8 Argentina ARG 0 Argentina ARG 0
## 9 Armenia ARM 0 Armenia ARM 0
## 10 Antigua and Barbuda ATG 0 Antigua and Barbuda ATG 0
## name name_long brk_a3 brk_name
## 1 S. Sudan South Sudan SDS S. Sudan
## 2 Afghanistan Afghanistan AFG Afghanistan
## 3 Angola Angola AGO Angola
## 4 Anguilla Anguilla AIA Anguilla
## 5 Albania Albania ALB Albania
## 6 Andorra Andorra AND Andorra
## 7 United Arab Emirates United Arab Emirates ARE United Arab Emirates
## 8 Argentina Argentina ARG Argentina
## 9 Armenia Armenia ARM Armenia
## 10 Antigua and Barb. Antigua and Barbuda ATG Antigua and Barb.
## brk_group abbrev postal formal_en formal_fr note_adm0
## 1 <NA> S. Sud. SS Republic of South Sudan <NA> <NA>
## 2 <NA> Afg. AF Islamic State of Afghanistan <NA> <NA>
## 3 <NA> Ang. AO People's Republic of Angola <NA> <NA>
## 4 <NA> Ang. AI <NA> <NA> U.K.
## 5 <NA> Alb. AL Republic of Albania <NA> <NA>
## 6 <NA> And. AND Principality of Andorra <NA> <NA>
## 7 <NA> U.A.E. AE United Arab Emirates <NA> <NA>
## 8 <NA> Arg. AR Argentine Republic <NA> <NA>
## 9 <NA> Arm. ARM Republic of Armenia <NA> <NA>
## 10 <NA> Ant.B. AG Antigua and Barbuda <NA> <NA>
## note_brk name_sort name_alt mapcolor7 mapcolor8 mapcolor9
## 1 <NA> South Sudan <NA> 1 3 3
## 2 <NA> Afghanistan <NA> 5 6 8
## 3 <NA> Angola <NA> 3 2 6
## 4 <NA> Anguilla <NA> 6 6 6
## 5 <NA> Albania <NA> 1 4 1
## 6 <NA> Andorra <NA> 1 4 1
## 7 <NA> United Arab Emirates <NA> 2 1 3
## 8 <NA> Argentina <NA> 3 1 3
## 9 <NA> Armenia <NA> 3 1 2
## 10 <NA> Antigua and Barbuda <NA> 2 2 5
## mapcolor13 pop_est gdp_md_est pop_year lastcensus gdp_year
## 1 5 10625176 13227.0 NA 2008 NA
## 2 7 28400000 22270.0 NA 1979 NA
## 3 1 12799293 110300.0 NA 1970 NA
## 4 3 14436 108.9 NA NA NA
## 5 6 3639453 21810.0 NA 2001 NA
## 6 8 83888 3660.0 NA 1989 NA
## 7 3 4798491 184300.0 NA 2010 NA
## 8 13 40913584 573900.0 NA 2010 NA
## 9 10 2967004 18770.0 NA 2001 NA
## 10 5 85632 1657.0 NA 2011 NA
## economy income_grp wikipedia fips_10 iso_a2
## 1 7. Least developed region 5. Low income NA <NA> SS
## 2 7. Least developed region 5. Low income NA <NA> AF
## 3 7. Least developed region 3. Upper middle income NA <NA> AO
## 4 6. Developing region 3. Upper middle income NA <NA> AI
## 5 6. Developing region 4. Lower middle income NA <NA> AL
## 6 2. Developed region: nonG7 2. High income: nonOECD NA <NA> AD
## 7 6. Developing region 2. High income: nonOECD NA <NA> AE
## 8 5. Emerging region: G20 3. Upper middle income NA <NA> AR
## 9 6. Developing region 4. Lower middle income NA <NA> AM
## 10 6. Developing region 3. Upper middle income NA <NA> AG
## iso_a3 iso_n3 un_a3 wb_a2 wb_a3 woe_id adm0_a3_is adm0_a3_us adm0_a3_un
## 1 SSD 728 728 SS SSD NA SSD SDS NA
## 2 AFG 004 004 AF AFG NA AFG AFG NA
## 3 AGO 024 024 AO AGO NA AGO AGO NA
## 4 AIA 660 660 <NA> <NA> NA AIA AIA NA
## 5 ALB 008 008 AL ALB NA ALB ALB NA
## 6 AND 020 020 AD ADO NA AND AND NA
## 7 ARE 784 784 AE ARE NA ARE ARE NA
## 8 ARG 032 032 AR ARG NA ARG ARG NA
## 9 ARM 051 051 AM ARM NA ARM ARM NA
## 10 ATG 028 028 AG ATG NA ATG ATG NA
## adm0_a3_wb continent region_un subregion
## 1 NA Africa Africa Eastern Africa
## 2 NA Asia Asia Southern Asia
## 3 NA Africa Africa Middle Africa
## 4 NA North America Americas Caribbean
## 5 NA Europe Europe Southern Europe
## 6 NA Europe Europe Southern Europe
## 7 NA Asia Asia Western Asia
## 8 NA South America Americas South America
## 9 NA Asia Asia Western Asia
## 10 NA North America Americas Caribbean
## region_wb name_len long_len abbrev_len tiny homepart
## 1 Sub-Saharan Africa 8 11 7 NA 1
## 2 South Asia 11 11 4 NA 1
## 3 Sub-Saharan Africa 6 6 4 NA 1
## 4 Latin America & Caribbean 8 8 4 NA NA
## 5 Europe & Central Asia 7 7 4 NA 1
## 6 Europe & Central Asia 7 7 4 5 1
## 7 Middle East & North Africa 20 20 6 NA 1
## 8 Latin America & Caribbean 9 9 4 NA 1
## 9 Europe & Central Asia 7 7 4 NA 1
## 10 Latin America & Caribbean 17 19 6 4 1
## geometry
## 1 MULTIPOLYGON (((33.95918 9....
## 2 MULTIPOLYGON (((74.89131 37...
## 3 MULTIPOLYGON (((14.19082 -5...
## 4 MULTIPOLYGON (((-63.00122 1...
## 5 MULTIPOLYGON (((20.06396 42...
## 6 MULTIPOLYGON (((1.706055 42...
## 7 MULTIPOLYGON (((53.92783 24...
## 8 MULTIPOLYGON (((-64.54917 -...
## 9 MULTIPOLYGON (((45.55234 40...
## 10 MULTIPOLYGON (((-61.71606 1...world <- world %>%
left_join(host_counts, by = c("name_long" = "Host"))
world$Count[is.na(world$Count)] <- 0
pal <- colorNumeric("YlOrRd", domain = world$Count)
leaflet(data = world) %>%
addTiles() %>%
addPolygons(
fillColor = ~pal(Count),
weight = 1,
opacity = 1,
color = "white",
dashArray = "3",
fillOpacity = 0.7,
highlight = highlightOptions(
weight = 3,
color = "#666",
dashArray = "",
fillOpacity = 0.7,
bringToFront = TRUE
),
label = ~paste(name_long, ": ", Count, " times hosted"),
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto"
)
) %>%
addLegend(
pal = pal,
values = ~Count,
opacity = 0.7,
title = "Times Hosted",
position = "bottomright"
)